Teaching computers to fold proteins - sprookjes - yvandenbroek - TriplyDB

Teaching computers to fold proteins

Teaching computers to fold proteins

http://www.wikidata.org/entity/Q21686181

about

sameAs

Sampling realistic protein conformations using local structural bias A generative, probabilistic model of local protein structure Probabilistic models and machine learning in structural bioinformatics.Protein side chain modeling with orientation-dependent atomic force fields derived by series expansions Efficient Parameter Estimation of Generalizable Coarse-Grained Protein Force Fields Using Contrastive Divergence: A Maximum Likelihood Approach.Experimental parameterization of an energy function for the simulation of unfolded proteins.Learning about protein hydrogen bonding by minimizing contrastive divergence.

P2860

Q21563518-489AF69B-974C-471E-8DA6-6623BA14DDEA Q24650447-EE4C93EC-1541-4043-9D7F-1998297818BC Q30374428-2EDE1410-133E-4D80-9453-AE810B8A05AD Q30400418-332F3F6E-926D-450F-B147-1E178DB8F381 Q38526771-22EEDEAC-7AEE-4136-B8B9-0F73B9A61259 Q41960727-43791BA7-B612-474B-862D-3A242EDA3A0F Q43711450-9B2B87BC-E9EC-4BF6-9DE3-6F5AC4D45383

P2860

Teaching computers to fold proteins

http://www.wikidata.org/entity/Q21686181

description

2004 nî lūn-bûn

@nan

2004 թուականի Սեպտեմբերին հրատարակուած գիտական յօդուած

@hyw

2004 թվականի սեպտեմբերին հրատարակված գիտական հոդված

@hy

2004年の論文

@ja

2004年論文

@yue

2004年論文

@zh-hant

2004年論文

@zh-hk

2004年論文

@zh-mo

2004年論文

@zh-tw

2004年论文

@wuu

name

Teaching computers to fold proteins

@ast

Teaching computers to fold proteins

@da

Teaching computers to fold proteins

@de

Teaching computers to fold proteins

@en

Teaching computers to fold proteins

@en-gb

Teaching computers to fold proteins

@fo

Teaching computers to fold proteins

@fr

Teaching computers to fold proteins

@is

Teaching computers to fold proteins

@kl

Teaching computers to fold proteins

@nb

type

label

Teaching computers to fold proteins

@ast

Teaching computers to fold proteins

@da

Teaching computers to fold proteins

@de

Teaching computers to fold proteins

@en

Teaching computers to fold proteins

@en-gb

Teaching computers to fold proteins

@fo

Teaching computers to fold proteins

@fr

Teaching computers to fold proteins

@is

Teaching computers to fold proteins

@kl

Teaching computers to fold proteins

@nb

prefLabel

Teaching computers to fold proteins

@ast

Teaching computers to fold proteins

@da

Teaching computers to fold proteins

@de

Teaching computers to fold proteins

@en

Teaching computers to fold proteins

@en-gb

Teaching computers to fold proteins

@fo

Teaching computers to fold proteins

@fr

Teaching computers to fold proteins

@is

Teaching computers to fold proteins

@kl

Teaching computers to fold proteins

@nb

P1104

Q21686181-800f3c62-43f0-74b6-9d86-acaa7222b5b7

P1433

Q21686181-A2562370-DEE0-42B8-8928-17B63B9D35D8

P1476

Q21686181-10F2EB52-FC7B-4857-AB45-D3A4AE53F0E9

P2860

Q21686181-0836C07C-5164-4DB2-A815-21109449920B

Q21686181-0877DEDB-55F4-422C-A2F1-9217F4CDDF93

Q21686181-0F96FABB-F845-47F4-9EB6-83405201E78A

Q21686181-10209CFB-B4F4-4807-B766-274BCD0B95F0

Q21686181-15D07846-D6E1-4354-B519-A344AAE62537

Q21686181-305CCA70-84A8-4F15-95C8-5E769A293E1C

Q21686181-45985E0A-8C9F-4FF7-B444-53467340CDC6

Q21686181-5A59B59A-7AF3-4534-B990-149384FBA440

Q21686181-611738A5-37D7-4E09-944C-43D7EED4B72F

Q21686181-6EC192D8-1862-4405-A965-117FC7549849

P304

Q21686181-36678EDB-FC92-41F9-95B2-22CE4A67DEBF

P31

Q21686181-85F3DFC8-7187-467D-8737-D6BD5701DF19

P356

Q21686181-6011906D-99ED-4680-9F5C-54282F71EAED

P407

Q21686181-CFCE6252-31B5-40CA-A2F5-1786184601C5

P433

Q21686181-4E1F4C18-E68D-44F1-B5AB-6FCF38791537

P478

Q21686181-088B9543-6033-489A-9B72-5BEDFCF6EFFF

P50

Q21686181-3a54215d-4da5-b6a9-8b9f-cef9169aa68c

Q21686181-F6396B9C-37AF-4C62-A6FF-4F18DE7CD424

P577

Q21686181-71363770-B17C-4108-B03C-25947E6E0C5A

P698

Q21686181-6AF2DF3C-8CDF-4CC2-9343-A4C214E978FD

P818

Q21686181-E69D946B-71AB-4CF2-901C-9422CC253600

P921

Q21686181-c44a4d8d-4680-cd82-b040-51714590c020

Q21686181-d3e3344d-4c0c-ccc4-bf27-3131d4850678

P356

PHYSREVE.70.030903

P1104

4

http://www.w3.org/2001/XMLSchema#decimal

P1433

Physical Review E

P1476

Teaching computers to fold proteins

@en

P2860

Rosetta in CASP4: progress in ab initio protein structure prediction

Principles that govern the folding of protein chains

How to derive a protein folding potential? A new approach to an old problem.

Protein folding simulations with genetic algorithms and a detailed molecular description.

An all-atom distance-dependent conditional probability discriminatory function for protein structure prediction.

How to guarantee optimal stability for most representative structures in the Protein Data Bank.

A method for parameter optimization in computational biology.

Three-helix-bundle protein in a Ramachandran model.

A statistical mechanical method to optimize energy functions for protein folding.

Optimal protein-folding codes from spin-glass theory.

P304

030903

http://www.w3.org/2001/XMLSchema#string

P31

scholarly article

P356

10.1103/PHYSREVE.70.030903

http://www.w3.org/2001/XMLSchema#string

P407

P433

3

http://www.w3.org/2001/XMLSchema#string

P478

70

http://www.w3.org/2001/XMLSchema#string

P50

P577

2004-09-01T00:00:00Z

http://www.w3.org/2001/XMLSchema#dateTime

P698

15524499

http://www.w3.org/2001/XMLSchema#string

P818

cond-mat/0309497

http://www.w3.org/2001/XMLSchema#string

P921

machine learning

protein folding